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School feeding programs for improving the physical and psychological health of school children experiencing socioeconomic disadvantage

2025· review· en· W4417211013 on OpenAlexaffabout
Elizabeth Kristjansson, Michael Dignam, Anita Rizvi, Mohamad Osman, Olivia Magwood, Deborah A. Olarte, Juliana F.W. Cohen, Julia Krasevec, Theresa R. Grover, Patrick Labelle, J.A. Garner, Laura Janzen, Sydney Rossiter, Omar Dewidar, Beverley Shea, Vivian Welch, George A. Wells

Bibliographic record

VenueCochrane Database of Systematic Reviews · 2025
Typereview
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsOttawa Public HealthUniversity of TorontoCanadian Nutrition SocietyHospital for Sick ChildrenCanadian Library AssociationCochraneBruyèreUniversity of Ottawa
Fundersnot available
KeywordsDisadvantageSocioeconomic statusProtocol (science)Psychological healthPsychological well-beingMental healthPublic health

Abstract

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RATIONALE: School feeding aims to alleviate hunger and enhance child outcomes. Since the first Cochrane systematic review of school meals, there has been a marked increase in studies and reviews of school feeding programs. However, most systematic reviews are geographically limited and use qualitative analysis. We reviewed worldwide papers and performed several meta-analyses, providing a more comprehensive picture of the effectiveness of school feeding. OBJECTIVES: 1. To assess effectiveness of school feeding programs for improving the physical and psychological health of children experiencing socioeconomic disadvantage worldwide. 2. To assess effectiveness of school feeding programs for improving the health of children experiencing socioeconomic disadvantage compared with children who are more advantaged. SEARCH METHODS: We searched 17 subject-specific and multidisciplinary databases and registries up to November 2023. In November 2024, two Information Specialists ran a top-up search for randomized controlled trials (RCTs). We handsearched references of included studies and relevant reviews. ELIGIBILITY CRITERIA: We included individually randomized, cluster-randomized, and cross-over trials, as well as longitudinal non-randomized studies of interventions (NRSIs). Studies had to compare the provision of free or reduced-price food in schools versus no school feeding, focusing on socioeconomically disadvantaged children. The food had to contain at least 3% of the daily energy requirement and at least 10% of the daily protein requirement for the specified age group(s). Eligible participants were primary or secondary school students aged five to 19 years. OUTCOMES: Our critical outcomes were change in: math achievement, reading achievement, attendance, enrollment, height-for-age z-score (HAZ), weight-for-age z-score (WAZ), and overweight/obesity. Our important outcomes were change in: overall academic achievement, fluid intelligence, working memory, behavioral/emotional outcomes, height, weight, and anemia. We planned to study changes between baseline and final outcomes. In one study with extreme contamination, we used the first follow-up. RISK OF BIAS: We assessed the risk of bias for RCTs by outcome using the appropriate version of the Cochrane risk of bias tool (RoB 2): RoB 2 for individually randomized trials, for cluster-RCTs, and for cross-over trials. We evaluated the quality of NRSIs using the School-based Measurement & Assessment of Results Tool (SMART), which is adapted from the Newcastle Ottawa Scale. SYNTHESIS METHODS: We used standardized mean differences (SMDs) with 95% confidence intervals (CIs) for educational and cognitive outcomes. We used mean differences (MDs), odds ratios (ORs), or incidence rate ratios (IRRs) for others. All meta-analyses used random-effects generic inverse variance. We conducted equity subgroup analyses by sex and socioeconomic status. We used GRADE to assess our confidence in the evidence for critical outcomes reported in RCTs. INCLUDED STUDIES: We included 40 studies with 83 reports. There were 13 RCTs (12 cluster-randomized trials and one individually randomized trial) and 27 NRSIs. Most studies (34) were from low- and middle-income countries (LMICs). In total, there were more than 91,885 students (four studies didn't report sample size). One study involved 59,613 students, while the others had between 60 and 6038 students. The studies included 48 outcomes; we meta-analyzed or reported 14. SYNTHESIS OF RESULTS: = 0%; 3 cluster-RCTs, 2132 participants; moderate-certainty evidence). Two cluster-RCTs assessed change in obesity/overweight. One 10-month study found that the odds of being overweight/obese were 53% lower among adolescents receiving school meals compared to control adolescents (OR 0.47, 95% CI 0.30 to 0.72). Another study found no cases of overweight/obesity before or after the intervention. These findings are of very low certainty. Some researchers encountered implementation problems beyond their control, including conflicts, delays, and bureaucratic decisions. Heterogeneity in contexts, outcomes, child populations, and statistics was a limitation of this review. High-income countries (HICs) One NRSI found very uncertain evidence that children assigned to a breakfast club increased their attendance by more than 1.6% on average compared to children in the control group. Equity analyses The equity (subgroup) analyses by sex and by socio-economic status were all non-significant. There were only two studies in each subgroup analysis; they were likely underpowered. AUTHORS' CONCLUSIONS: In LMICs, school feeding programs lead to a slight improvement in math achievement, but may have little to no effect on reading achievement. School feeding programs lead to a slight increase in enrollment, but may have little to no impact on attendance. They likely lead to slight gains in HAZ and WAZ. There may be little to no association between school feeding and overweight/obesity, but the evidence is very uncertain. We recommend that researchers and policymakers view research as an integral part of the implementation process. To reduce heterogeneity in outcomes, we recommend even greater co-ordination of research, and that researchers and interest holders work together to identify a core set of outcomes. FUNDING: The authors would like to thank the following donors for their generous support in making this review possible: Dubai Cares, the World Food Programme's School Meals and Social Protection Service, and the Research Consortium for School Health and Nutrition. REGISTRATION: Protocol (2022): https://doi.org/10.1002/14651858.CD014794 Original review (2007): https://doi.org/10.1002/14651858.CD004676.pub2 Original Campbell protocol (2006): doi.org/10.1002/CL2.12.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.027
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0060.004
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0140.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.098
GPT teacher head0.426
Teacher spread0.329 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2025
Admission routes2
Has abstractyes

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